


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE     :					Optional[Any]      =       logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE     :					List[str]      =       {
    "google/mobilenet_v2_1.4_224": "https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json",
    "google/mobilenet_v2_1.0_224": "https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json",
    "google/mobilenet_v2_0.75_160": "https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json",
    "google/mobilenet_v2_0.35_96": "https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}

class     A__   (       snake_case__      ):







    """simple docstring"""

    __magic_name__         =						'mobilenet_v2'
    def __init__(			self     ,   __snake_case=3     ,   __snake_case=2_2_4     ,   __snake_case=1.0     ,   __snake_case=8     ,   __snake_case=8     ,   __snake_case=6     ,   __snake_case=3_2     ,   __snake_case=True     ,   __snake_case=True     ,   __snake_case="relu6"     ,   __snake_case=True     ,   __snake_case=0.8     ,   __snake_case=0.02     ,   __snake_case=0.001     ,   __snake_case=2_5_5     ,   **__snake_case     ,   ):
         super().__init__(**__snake_case       )

         if depth_multiplier <= 0:
              raise ValueError('''depth_multiplier must be greater than zero.'''       )

         snake_case											=							num_channels
         snake_case											=							image_size
         snake_case											=							depth_multiplier
         snake_case											=							depth_divisible_by
         snake_case											=							min_depth
         snake_case											=							expand_ratio
         snake_case											=							output_stride
         snake_case											=							first_layer_is_expansion
         snake_case											=							finegrained_output
         snake_case											=							hidden_act
         snake_case											=							tf_padding
         snake_case											=							classifier_dropout_prob
         snake_case											=							initializer_range
         snake_case											=							layer_norm_eps
         snake_case											=							semantic_loss_ignore_index






class     A__   (       snake_case__      ):







    """simple docstring"""

    __magic_name__         =						version.parse('1.11'      )
    @property
    def 						a_     (			self       ):
         return OrderedDict([('''pixel_values''', {0: '''batch'''})]       )
    @property
    def 						a_     (			self       ):
         if self.task == "image-classification":
              return OrderedDict([('''logits''', {0: '''batch'''})]       )
         else:
              return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]       )




    @property
    def 						a_     (			self       ):
         return 1E-4








import requests

_SCREAMING_SNAKE_CASE     :					Optional[int]      =       ""  # <-- Put your OpenWeatherMap appid here!
_SCREAMING_SNAKE_CASE     :					Optional[Any]      =       "https://api.openweathermap.org/data/2.5/"
def      UpperCAmelCase__		(UpperCamelCase_ = "Chicago"				,UpperCamelCase_ = APPID							):



     """simple docstring"""






     return requests.get(URL_BASE + '''weather'''				,params=locals()							).json()
def      UpperCAmelCase__		(UpperCamelCase_ = "Kolkata, India"				,UpperCamelCase_ = APPID							):



     """simple docstring"""






     return requests.get(URL_BASE + '''forecast'''				,params=locals()							).json()
def      UpperCAmelCase__		(UpperCamelCase_ = 55.68				,UpperCamelCase_ = 12.57				,UpperCamelCase_ = APPID							):



     """simple docstring"""






     return requests.get(URL_BASE + '''onecall'''				,params=locals()							).json()


if __name__ == "__main__":
 from pprint import pprint

 while True:
  _SCREAMING_SNAKE_CASE     :					Any      =       input("Enter a location:").strip()
  if location:
   pprint(current_weather(location))
  else:
   break




